Abstract:
Economic growth is often not distributed uniformly across a country or state. This
provides obligation to governments to provide assistance, such as grants, to reduce economic
inequality between subregions. This thesis investigates how the allocation of Ohio state grant
funding impacts economic development between counties. Data were retrieved from archival
data sets available between the years 2010 through 2014. The data were analyzed to consider the
spatial interaction between counties as the economic activity within cities can impact the
economic activity in surrounding rural areas (Henry & Drabenstott, 1996). First, an OLS
regression was conducted for each year of data and analyzed to determine if spatial
autocorrelation was present. Then, spatial effects were captured by conducting regressions
utilizing the spatial error model, the spatial lag model, and the spatial Durbin model. The spatial
models and OLS model were compared using their AIC and BIC values. The results suggest
spatial regression was not preferred to OLS in modeling the impact of grant funding, in the years
2010 through 2014. Additionally, according to our model, grant funding over the 5-year period
had a small and statistically non-significant impact on overall economic activity in Ohio.
However, the results also indicate spatial regression will likely continue to become more
important in the analysis of grant funding due to both the theoretical implications and the
presence of growing spatial economic inequality. This study opens several avenues for future research such as the substitution of the one-year and 5-year growth rates of real GDP per capita
for the dependent variable and investigating the trend of spatial autocorrelation in years after
2014.
